PhD Position on Embodied World Models

Are you interested in performing high-impact artificial intelligence research on embodied world models that will enable an autonomous robot to operate in an open world

Join Us!

Progress in multimodal world models has been astonishing in the past few years and allow to equip robots with world knowledge of scenes objects and human activities. Robots should then be able to perceive and act upon the sensed world be it that current solutions require data diversity task circumstances and the label vocabulary all to be pre-defined stationary and controlled. As soon as these closed world deep learning assumptions are broken perceptual understanding suffers and oftentimes catastrophically. Hence robots equipped with state-of-the-art multimodal perceptual skills will experience great difficulty generalizing to perception tasks in an open world where sensory and semantic conditions will differ considerably from those perceived during training. Our key research question is: How to enable multimodal perception for robots that is robust to sensory and semantic shifts between training and operation conditions

This is what you will do

You will carry out research and development in the areas of embodied world models deep machine learning and computer vision. Potential topics of interest are test-time generalization embodied grounding data scarcity and uncertainly modeling. The research is embedded in the VIS lab at the University of Amsterdam and you will actively collaborate within the OpenBots lab that contains a PhD and Postdoc at the University of Amsterdam and three PhD students at Delft University of Technology (focusing on robot planning and control). The lab is further supported by researchers and robots from project partners TNO and the Royal Netherlands Marechaussee. The project is carried out with supervisors from the Video and Image Sense Lab (Amsterdam) and the Cognitive Robotics Group (Delft). The team at UvA will be supervised by prof. dr. Cees Snoek and dr. ir. Gertjan Burghouts (TNO).

Your tasks will be to:

• Develop new deep learning computer vision and multimodal learning methods on embodied world models.
• Actively collaborate within the OpenBots Lab and contribute to its demonstrators.
• Regularly present internally on your progress.
• Regularly present intermediate research at international conferences and workshops publish them in proceedings and journals.
• Assist in teaching activities such as lab assistance and student supervision.
• Complete and defend a PhD thesis within the official appointment duration of four years.

What we ask of you

• An MSc degree in Artificial Intelligence (Applied) Mathematics/Physics Computer Science Engineering or related field.
• A strong background/knowledge in machine learning and computer vision knowledge of robotics is a plus but not required.
• Solid mathematics foundations especially statistics calculus and linear algebra;
• Excellent programming skills preferably in Python.
• You are highly motivated independent and creative.
• Strong communication presentation and writing skills and excellent command of English.
• Prior publications in relevant machine learning or computer vision conferences or journals are advantageous.

This is what we offer you

A temporary contract for 38 hours per week for the duration of 4 years (the initial contract will be for a period of 18 months and after satisfactory evaluation it will be extended for a total duration of 4 years).The preferred starting date is as soon as should lead to a dissertation (PhD thesis). We will draft an educational plan that includes attendance of courses and (international) meetings. We also expect you to assist in teaching undergraduates and master students.

The gross monthly salary based on 38 hours per week and dependent on relevant experience ranges between 3059 to 3881 (scale P). This does not include 8% holiday allowance and 83% year-end allowance. The UFO profile Promovendus is applicable. For this position we can not sponsor a visa. TheCollective Labour Agreement of Universities of the Netherlands is applicable.

Curious about our extensive secondary benefits package You can read more about it here.

You will work in this team

TheUniversity of Amsterdam (UvA) is the Netherlands largest university offering the widest range of academic programmes. At the UvA 42000 students 6000 staff members and 3000 PhD candidates study and work in a diverse range of fields connected by a culture of curiosity.

The Faculty of Science (FNWI) has a student body of around 8000 as well as 1800 members of staff working in education research or support services. Researchers and students at the Faculty of Science are fascinated by every aspect of how the world works be it elementary particles the birth of the universe or the functioning of the brain.

The position is with Prof. dr. Cees Snoek Professor head of theVideo & Image Sense lab (VIS lab) at the University of Amsterdam. VIS lab is a world-leading lab on Computer Vision and Machine Learning and has over 40 PhD students postdoctoral researchers and faculty members working on a broad variety of deep learning computer vision and foundation model subjects like self-supervised learning diffusion models and test-time generalization for perception tasks like object detection instance segmentation and activity recognition. The position is also embedded in the ELLIS Network of Excellence in AI.

Want to know more about our organisation Read more about working at the University of Amsterdam.

If you feel the profile fits you and you are interested in the job we look forward to receiving your application. You can apply online via the button below. We accept applications until and including March 13 2026.

If you have any questions or do you require additional information Please contact:

• Prof. dr. Cees Snoek
• Dr. ir. Gertjan Burghouts

Applications should include the following information (all files besides your cv should be submitted in one single pdf file):

• A letter that motivates your choice for this position;
• Curriculum vitae including your list of publications if applicable (max 2 pages);
• A research statement on how to approach the PhD project. Solid and creative ideas will be greatly appreciated. (max 2 pages).
• A link to your Master thesis if online available else include an abstract.
• A complete record of Bachelor and Master courses (including grades and explanation of grading system);
• A list of projects or publications you have worked on with brief descriptions of your contributions max 1 page;
• The names and contact addresses of at least two academic references (please do not include any recommendation letters).

Note that because our OpenBots partners TNO and the Royal Netherlands Marechaussee handle sensitive information a security investigation will be part of the application procedure. Applicants residig outside NATO countries will not be considered.